omics integration, reproducible research, mass spectrometry, proteomics, peptidomics, metabolomics, workflow, Galaxy, microservices, Kubernetes
| payam.emami@nbis.se |
|---|
Payam received his Ph.D. in medical bioinformatics from the Uppsala University in 2017 where he worked on various bioinformatics projects mainly focusing on mass spectrometry (MS)-based proteomics, peptidomics, and metabolomics. The projects ranged from simple label-free proteomics to more sophisticated labeled/unlabelled experiments. In 2015, Payam joined the PhenoMeNal consortium where he worked on a variety of metabolomics projects including cloud-based metabolite identification and quantification tools/workflows.
In 2018, Payam started his Postdoc at Karolinska Institute where he primarily worked on the MS-based identification of intact (neuro)peptides. This includes designing and evaluating computational tools/workflows to facilitate automatic de novo and database-based characterization of intact peptides.
Payam mainly supports start to end pre-processing and statistical analyzing of various MS experiment. He also supports designing computational workflows for analyzing such data. His current research interests are proteomics, peptidomics, metabolomics, tool/workflow development, data integration, cloud-based data analysis, microservices-based architecture, Kubernetes-based workflows, Galaxy workflows, and reproducible data analysis.
omics integration, reproducible research, mass spectrometry, proteomics, peptidomics, metabolomics, workflow, Galaxy, microservices, Kubernetes
| payam.emami@nbis.se |
|---|
Payam received his Ph.D. in medical bioinformatics from the Uppsala University in 2017 where he worked on various bioinformatics projects mainly focusing on mass spectrometry (MS)-based proteomics, peptidomics, and metabolomics. The projects ranged from simple label-free proteomics to more sophisticated labeled/unlabelled experiments. In 2015, Payam joined the PhenoMeNal consortium where he worked on a variety of metabolomics projects including cloud-based metabolite identification and quantification tools/workflows.
In 2018, Payam started his Postdoc at Karolinska Institute where he primarily worked on the MS-based identification of intact (neuro)peptides. This includes designing and evaluating computational tools/workflows to facilitate automatic de novo and database-based characterization of intact peptides.
Payam mainly supports start to end pre-processing and statistical analyzing of various MS experiment. He also supports designing computational workflows for analyzing such data. His current research interests are proteomics, peptidomics, metabolomics, tool/workflow development, data integration, cloud-based data analysis, microservices-based architecture, Kubernetes-based workflows, Galaxy workflows, and reproducible data analysis.